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Models Using Clinical and Communication Data in British Columbia. The fellow will work with a diverse set of real-world datasets—including two-way patient–provider texting collected via the WelTel
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enhance provincial capacity to tailor care approaches in response to the ongoing substance use crisis. The ideal candidate will have a passion for integrating multiple sources of quantitative data and a
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) into the technical architecture and design choices of AI systems, particularly as they relate to data representation, ethical AI frameworks, and beneficial applications. Collaboration and Coordination: Working closely
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engagement, and educational activities to explore how modern information and communication technologies (e.g. mobile and web-based applications, sensors, wearables, AI/ML etc.) can improve health care. Digital
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generating unbiased, systematic data can give new and unexpected insights into biology. That has been at the core of our work ranging from genome-scale RNAi screens to systematic mapping of genetic
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undergraduate students Present data at individual and lab meetings, team meetings Present data at departmental and institutional trainee research days and external academic conferences Write manuscripts
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workflows, biological sample collection, biobank management (labeling, storage, retrieval) Coordinating multi-laboratory analytical workflows and ensure method validation and documentation. Working with
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) using syndemic and precision public health approaches. This project will use data from the BC Hepatitis Testers Cohort (BC-HTC) and IDEALs Cohorts- longitudinal cohorts of ~2.5 million people tested
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data